DataVisor Global Fraud Watch: November 2020 Edition

Meta: As the end of the year draws closer, it’s important to remember that fraud never takes a holiday. Here are some recent examples of fraud cases.

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As the holiday shopping season begins, retailers know that consumers aren’t the only ones looking to cash in on good opportunities. Fraudsters are doing their part to keep companies on their toes by exploiting loyalty programs and offers, rerouting packages, taking over accounts, and stealing credit card information, among other fraudulent activities.

While shopping scams tend to take center stage during the holidays, it’s important to remember that other types of fraud still pose risks, too. …


Learn how your organization can increase fraud detection while continuing to deliver consistent omnichannel customer experiences.

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The fields of customer service and fraud prevention have evolved significantly over the years, and while they may have, at one time, been separate considerations, they are inextricably connected today. So much so, that balancing the two has emerged as a unique new challenge in our big data era. An ongoing question for organizations is how to simultaneously increase fraud detection without introducing customer friction.

The answer lies in the successful adoption of a centralized approach to data intelligence. By integrating and deploying advanced AI and machine learning-powered systems that enable holistic analysis and ensure consistent coverage and real-time responsiveness, organizations are able to maintain continuous, end-to-end engagement with their customers. …


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The idea behind “phishing” predates the internet by countless years. In its most basic form, it’s simply the act of impersonating someone to trick them out of something; money, information, anything of value.

Before crime went online, the kind of scam happened on the phone; someone would call you, lie about who they were, and try and get information from you; often using scare tactics; i.e., impersonating an authority figure, and threatening negative consequences if the requested information isn’t shared. A classic use case might be someone impersonating an IRS agent, to get you to divulge your social security number. …

Priya Rajan

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